Optical character recognition (OCR) systems are generally used to detect text present in an image and to convert the detected text into its equivalent electronic representation. Conventional OCR systems have relied on using a single image to detect and recognize text. Such OCR systems, when using a single image frame, often fail to recognize all text in the image as a result of poor lighting, contrast, focus conditions, and the like. Further, OCR systems typically require a minimum character size in order for the text to be properly recognized. Due to limited camera resolution, this means that many real-world documents, or other bodies of text, are too voluminous to be captured in a single image frame at a character size sufficiently large enough to be recognized by an OCR system. As technology advances and as people are increasingly using computing devices in a wider variety of ways, it can, therefore, be advantageous to adapt the ways in which text is captured, recognized, and processed using a computing device in order to enable users to capture and recognize larger bodies of text with the same.